The end of inertia: Agentic AI's disruption of retail and SME banking

Source: Ramji Sundararajan and Uzayr Jeenah, with Alana Ellis; McKinsey & Company · 2025-08-15

Agentic AI—technology that can perform tasks and solve issues largely on its own—will be able to handle complex requests like the one above, shifting AI from reactive helper to proactive financial agent for shopping, payments, and investing.

These developments are expected to shake up the economic foundations of finance, affecting billions in revenue and posing a threat to business models and revenue at banks, small and medium-size enterprises (SMEs), credit-card companies, and others. Pioneers willing to lead the way could see a game-changing upside, while those who don’t innovate will lose out. The changes will be felt first in markets where open banking has taken root.

Two revenue “engines”—credit cards and deposits—are especially exposed. Both rely heavily on customer inertia and brand familiarity. But AI agents won’t care about brand loyalty. They will optimize for outcomes. When logic, not habit, drives product selection, the rules will change.

OpenAI’s Operator Mode can already browse the web, make a hotel booking, and carry out multistep tasks. Start-ups like Manus AI and tools like Perplexity are pushing even further—working across business platforms, interpreting user intentions, and taking action. Google has introduced an AI Mode shopping experience that delivers personalized discovery and price tracking via Gemini AI. To facilitate these moves, payments players such as Visa, Mastercard, and PayPal have recently released new capabilities to facilitate agentic commerce, allowing agents to trigger payments autonomously on behalf of users.

The global payments industry generates more than $2.7 trillion in annual revenue from sources such as deposit spreads, card economics, cross-border flows, and merchant acquiring.

Both revenue engines rely on a simple truth: Most consumers don’t optimize every dollar, every day. Margin accrues in the gap between what consumers could do and what they actually do.

Agentic AI breaks that equation. Even partial adoption of the technology can meaningfully compress those margins or shift revenue to other businesses.

Deposits—from consumer checking to SME operating accounts—have long powered bank profitability. Globally, net interest income accounts for roughly 30 percent of retail-bank profit.

The national rate that banks pay on interest-bearing checking and savings accounts in the United States was just 0.07 and 0.38 percent, respectively, in June 2025, even though top online saving rates exceed 4 percent. Further, over the past five years, non-interest-bearing demand-deposit account balances grew at a CAGR of 28 percent, compared with just 3 percent for interest-bearing equivalents.

Agentic AI systems flip that logic. They can monitor balances in real time, compare returns across institutions, sweep idle cash into higher-yield accounts, and then sweep cash back to a checking account in time for bills. That allows more of the spreads once captured by banks to go to account holders.

By 2017, Yu’e Bao had become the world’s largest money-market fund, with about $268 billion in assets under management and more than 260 million users, many of whom had never actively invested before. It was an early example of embedded, agent-like behavior: automating financial optimization at the system level.

Yu’e Bao wasn’t labeled AI, but it showed what can happen when optimization is embedded at scale: rapid adoption, reduced friction, and new systemic risks. It is a cautionary blueprint for what agentic finance could enable—and what regulators may soon scrutinize.

The European revenue pool from deposits is worth more than $100 billion. If just 10 to 20 percent of consumers adopt agent-driven cash sweeps, bank net-interest margins could tighten by 30 to 50 basis points (bps).

Credit cards generate extraordinary revenue—$234 billion in 2024—through a blend of interest income from customers who carry a balance, interchange fees, annual and penalty fees, and unredeemed rewards (exhibit).

Much of this lucrative model is held together by consumer inertia. Recent survey data suggests that more than 20 percent of cardholders didn’t redeem any rewards in the prior 12 months. “Forfeiture incidence”—the share of accrued rewards points lost through account closure or expiration—ranges from 3 to 5 percent annually, according to the Consumer Financial Protection Bureau.